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Abstract
Decision governance in a joint human-machine systems allows application of human creativity alongside complex algorithm and knowledge searches by machines. In a decision making critical situation, this joint venture requires maximum certainty in order to overcome any mission failures. However, current progress in machine intelligence as well as existing research in the artificial intelligence community depends on the best practices and/or standards set forth by individual organizations and government responsible for the advancement of AI or MI. In absence of an expert reference base or knowledge base, more precisely a universal system, we still rely on the information and standards that differ from organization to organization and from government to government. This paper seeks to mitigate this systems gap by looking at a systematic approach in decision governance by developing various levels of ontologies for human-machine systems. In support of this proposed approach, a recent development of top ontology is discussed that revealed the core terminology and their relationships within human-machine systems. This existential understanding even lays the foundation for various other ontological evolution.
Keywords
Ontology, Knowledge Generation, Decision Governance, Human-Machine Systems
Introduction
Ontology and its exploitation in the field of engineering management (Mahmud and Zahedi, 2018) enforces: (1) identifying problem space from the existence level, (2) recognizing all relevant domains necessary to build the taxonomic and axiomatic structure for clarifying the structure of knowledge, and resulting in (3) better understanding about a domain of discourse to overcome any discernment. Until now, decision governance in a human-machine intelligence systems rely on the best practices and/or standards that differ from organization to organization and from government to government, contributing to systems failure in complex mission critical situations (Mahmud, 2018). Therefore, systematic approach in the form of ontological analysis is necessary to eradicate decision governance problems in any given decision situation.
Exhibit 1 (Mahmud and Cotter, 2017) summarizes the primary levels or types of ontologies based on the scope that are found in the existing literature. A foundational ontology is also referred to top or upper level ontology. This essentially gives the foundation of subsequent ontology development. The scope of a foundational ontology is to specify the general or universal classifications or categories, relations, and axioms for a body of knowledge such that these concepts...